Uniform Manifold Approximation and Projection

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

A curated list of community detection research papers with implementations.

Text Classification Algorithms: A Survey

Extensible, parallel implementations of t-SNE

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

A repository of pretty cool datasets that I collected for network science and machine learning research.

Minimum-distortion embedding with PyTorch

Machine Learning notebooks for refreshing concepts.

PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.

JavaScript implementation of UMAP

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

An R package implementing the UMAP dimensionality reduction method.

Dimensionality reduction in very large datasets using Siamese Networks

Functional Data Analysis Python package

An implementation of demixed Principal Component Analysis (a supervised linear dimensionality reduction technique)

Deep Learning sample programs using PyTorch in C++

Single cell trajectory detection

Using siamese network to do dimensionality reduction and similar image retrieval

Mathematical tools (interpolation, dimensionality reduction, optimization, etc.) written in C++11 with Eigen

MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).

Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)

The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.

A New, Interactive Approach to Learning Data Science

Hierarchical Uniform Manifold Approximation and Projection

t-Distributed Stochastic Neighbor Embedding (t-SNE) in Go

Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz

Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.

A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).